data1<-read.csv("clin_inf.csv",sep=" ")
data2<-read.csv("count.csv",sep=" ")
data3<-read.csv("exp_inf.csv",sep=" ")
data4<-read.csv("ID_annoation.csv",sep=" ")
a1<-merge(data3,data1,by.x=1,by.y=1)
data4$gene_id<-gsub("\\.\\d+$","",data4$gene_id)
data4.1<-data4
colnames(data2)<-gsub("^X","XYA",colnames(data2))
colnames(data2)<-gsub("XYA(....)$","PTB\\1",colnames(data2))
colnames(data2)<-gsub(".$","",colnames(data2))
colnames(data2)<-gsub("gene_i","gene_id",colnames(data2))
data4.1<-data4[match(data2$gene_id,data4$gene_id),]
match(data4.1$gene_id,data2$gene_id)
counts<-column_to_rownames(a1,"样本名称")
data<-data.frame(data2)
row.names(data)<-data[,1]
data4.2.1<-data[,-1]
data<-data.frame(data4.1)
row.names(data)<-data[,1]
data4.1.1<-data[,-1]
a1.1<-data.frame(a1)
row.names(a1.1)<-a1.1[,1]
a1.1<-a1.1[,-1]
install.packages("BiocManager")
options(BioC_mirror = "https://mirrors.ustc.edu.cn/bioc/")
BiocManager::install("Biobase")
library(Biobase)
phenoData <- AnnotatedDataFrame(data = a1.1)
featureData <- AnnotatedDataFrame(data = data4.1.1)
assayData <- as.matrix(data4.2.1)
rownames(phenoData) <- colnames(assayData)
expressionSet <- ExpressionSet(assayData = assayData, phenoData = phenoData, featureData = featureData)
